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Chapter 10 — Reference and Master Data

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CDMP Fundamentals weight: 10% — major domain
Source boundary: DAMA-DMBOK2 Revised, Chapter 10, pp. 329–359.

Chapter 10 is about creating shared enterprise context. Reference Data governs the controlled values used to classify and interpret other data. Master Data governs the persistent real-world entities—customers, products, locations, accounts, legal entities, and similar subjects—that many processes and systems reuse.

The chapter becomes much easier when you keep four questions separate:

  1. What kind of data is this? Reference, Master, Transaction, or Metadata?
  2. Where is authority? System of Record, System of Reference, Trusted Source, or a reconciled Golden Record?
  3. What identity action is needed? Flag, link, merge, assign identifiers, or manage relationships?
  4. How should shared data be distributed? Registry, Transaction Hub, Consolidated architecture, controlled Reference publication, or another governed sharing pattern?

Study route

  1. Guided Learning — build the mental model before memorizing terms.
  2. Exam Map — high-yield distinctions, traps, sequences, and readiness checks.
  3. Visual Memory Atlas — 12 redraw-first maps.
  4. Battle Cards — rapid and deep discrimination drills.
  5. Scenario Lab — apply the deciding clue under changed facts.
  6. Question Bank — 68 diagnostic MCQs with answer-separated rationale files.
  7. Teach-Back — retrieval, reconstruction, classification, and compression.

Core mental model

Transaction events involve Master entities and are interpreted with Reference values; Metadata describes meaning, source, stewardship, lineage, and lifecycle facts across all of them.

Then Chapter 10 adds the operating discipline:

Requirements → source assessment → architecture → enterprise model → preparation → identity resolution / controlled Reference change → sharing → stewardship → governance → metrics → improvement.

Highest-risk exam confusions

  • Reference Data vs Master Data
  • Master Data vs Transaction Data
  • Reference/Master Data vs Metadata
  • System of Record vs System of Reference
  • Trusted Source vs Golden Record
  • deterministic vs probabilistic matching
  • false positive vs false negative
  • duplicate identification vs match-link vs match-merge
  • Global ID vs Source ID vs X-Ref
  • Registry vs Transaction Hub vs Consolidated
  • standardization vs enrichment vs identity resolution
  • Data Sharing Agreement vs technical interface specification
  • SLA vs Data Quality rule
  • installed MDM tool vs functioning MDM program

Artifact 08 rule: Chapter Review / Error Repair is intentionally absent until real study performance exists. Only actual misses, slow decisions, confidence errors, and repeated confusion should populate it.

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